Liver disease diagnosis and treatment represents a significant cost to the United States health care system. Chronic liver disease and cirrhosis affects over 2,600,000 people in the United States, leading to over 700,000 hospitalizations annually. Chronic liver diseases progress over several decades at an estimated annual cost of $1.3 billion. Definitive diagnosis of liver disease is performed by liver biopsy; however, this invasive procedure has associated risks and is not well tolerated by patients. As a result, frequent staging of disease progression is not possible, and non-specific blood tests are often used as surrogates for biopsy to determine hepatic fibrosis stage. A separate challenge for liver disease diagnosis involves characterization of focal lesions. Focal liver lesions are detected during ultrasound imaging studies both incidentally and in patients who have an underlying malignancy. Distinguishing benign from malignant lesions with ultrasound is challenging, and many patients with lesions discovered during sonograms are referred for contrast enhanced CT or MRI for further characterization. These additional imaging studies are expensive and require additional patient visits, and they increase patient anxiety. The long term goal of this research i to develop an ultrasonic, quantitative acoustic radiation force impulse (ARFI) based elastography imaging system capable of noninvasive staging of liver fibrosis and differentiation between benign and malignant liver lesions. We propose the development of novel algorithms and beam sequences using both simulation and experimental tools to achieve the required spatial resolution, accuracy, and precision. There are three specific aims: 1) To develop and implement novel stiffness reconstruction methods combining qualitative and quantitative ARFI technologies to provide structurally accurate quantitative stiffness estimates and images of hepatic tumors. 2) To develop and implement 3D shear wave speed monitoring beam sequences and algorithms using a 2D matrix array to improve the accuracy and precision of shear wave speed estimates, and 3) To evaluate this next-generation system in the context of hepatic fibrosis staging and hepatic tumor characterization.